observed variables, x . However, there may also be unobserved sources of
t
heterogeneity. The standard way of trying to deal with this problem is to assume that an unobserved random variable ´ , which is time constant and independent of
Ž .
the observed covariates, enters the hazard multiplicatively. Eq. 2.2
is thus changed to
r t ,x s u t exp x
X
b ´ , 2.6
Ž .
Ž . Ž
. Ž
.
With an additional assumption regarding the distribution of this unobserved variable,
9
such a model can be estimated. Usually a gamma distribution is chosen. Ž
. Meyer 1990 implemented this approach in the semiparametric model. It may be
shown
10
that when ´ is gamma distributed with unit mean and variance s
2
, the log-likelihood function becomes
y2
ys
t y1 n
i
X 2
log L s log
1 q s exp x b q g
Ž .
Ý Ý
t t
½
is1 ts1
y2
ys
t
i
X 2
yd 1 q s exp x b q g
. 2.7
Ž .
Ž .
Ý
i t
t
5
ts1
Results from both specifications will be reported in this paper.
11
One final modification of the model is made: we ask whether the hazard increases as benefit exhaustion approaches. To include this aspect in the analysis,
UB
Ž we define I s 1 if benefits are received, 0 otherwise, and replace g by g
q 1
t t
.
nonUB
y I g . The interval length is four weeks, corresponding to the accuracy with
t
which the spells are measured in the unemployment register.
3. Data
Unemployment insurance is compulsory for all employees in Norway. The premium is included in the contribution to the social insurance system. Employees
with earnings above a certain minimum level during the last three years who lose their jobs involuntarily, are entitled to unemployment benefits amounting to 62
of the previous year’s wage income. To obtain benefits, one has to register at the local employment agency and be available for new placement. The agencies offer
guidance of various sorts, and access to labour market programmes. These services
9
Ž Alternatively, the distribution can be approximated nonparametrically
Heckman and Singer Ž
.. 1984 .
10
Ž .
Ž .
See Meyer 1990 or Dolton and van der Klaauw 1995 .
11
The choice of a gamma distribution for the error term is made for computational reasons, and may Ž
. be debatable. Cf. the discussion in Narendranathan and Stewart 1993b .
are available also to those who are not entitled to benefits, e.g., first entrants to the labour market. Therefore, even individuals without benefit entitlement have some
incentives to register. Beneficiaries who stop reporting lose their benefits. Our two data sets are drawn from the
KIRUT
12
database, which collects extensive information from various administrative registers for a 10 random
sample of the Norwegian working aged population. The data, linked with personal identifiers, are organised in an event-oriented fashion, and presently covers the
period from 1989 until 1994, inclusive. Data providers are the Directorate of Labour, the National Insurance Administration, and Statistics Norway. Using
register data has obvious advantages. At relatively low costs, the researcher gets access to large amounts of data on the individual level. The problems with sample
dropouts so often encountered in surveys, are to a large extent avoided. Also, the researcher is able to construct case histories based on information collected for
bureaucratic reasons, rather than relying on individual retrospection. Some exactly recorded information, e.g. related to earnings histories, may be less precisely
recalled by the individuals themselves. Admittedly, using register data also has its problems, which we shall go into in the next paragraphs. To a large extent they are
related to the fact that the records are generated for other purposes than research.
Our sampling strategy is to use two samples of individuals who face different rules with respect to UB duration, but similar labour market conditions. The first
sample was constructed by picking everybody in the database who started report- ing as unemployed at the public employment agencies from June 1 through
December 1, 1990, and the second sample consists of people that started reporting in the same period the next year. The samples include several dates pertaining to
change of labour force status, where the two most important are: the day a person left the unemployment register, and the day he was recorded in the employers’
register.
13
The data from the unemployment register cover the length of the Ž
. current spell, and succeeding spells up to December 31, 1992 1993 for data set 1
Ž . 2 . From the employers’ register, we have records of all spells that started after
Ž .
the unemployment spell and before December 31, 1992 1993 . We remind the reader that the UB withdrawal period after 80 weeks was abolished in May 1992.
Consequently, the reform affected the search incentives around benefits expiration for the second group, but not the first. As for the beginning of the unemployment
period, the incentive effects for the second group are less clear. Until May 1992, people from both groups were faced with identical UB rules. However, to the
extent that the unemployed in the second group knew the content of the reform before it was passed by the Parliament, we must assume that their expectations to
12
This Norwegian acronym roughly translates to ‘‘Clients into and through the Social Insurance system’’.
13
Employers are obliged to report to this register all new employees who are expected to stay in the job for at least 6 days. The register does not include the self-employed and seamen.
the coming reform might have had disincentive effects on their search behaviour right from the beginning of their unemployment period. A sample based on people
reporting as unemployed after the reform of May 1992 and followed through 1994 would cast light on this assumption, but was not available at the time when
the research was conducted.
Sampling from the unemployment registers may underestimate the number of persons who would like to have a job if they could get one, i.e. who are in the
labour force but out of work. Presumably, that would mainly be individuals without benefit entitlement. If one chooses to use register data, this problem
remains anyway. Furthermore, given the available registers, the duration of an unemployment spell could be defined in several ways. First, the duration could
simply be defined as the time spent in the unemployment register. Then we would not know if the spell ended with a transition to employment or out of the labour
force. The individual could also stop registering, e.g., because he was not entitled to benefits, but still be a job seeker. Alternatively, the length of a spell could be
defined as the time from the unemployment register record started until the individual was recorded in the employer’s register. A new problem introduced by
Ž this approach is that individuals who spent time out of the labour force e.g.,
. education, young males in the military services, females having children etc. may
be perceived as having a continuous spell of unemployment. It seems fairly obvious that the first approach may underestimate the true unemployment dura-
tion, and the second may overestimate it. The problem may be alleviated by combining the registers, only counting transitions directly from the unemployment
register into the employers’ register as transitions, and treating unemployment records ending without an according employment record as censored. This defini-
tion may still be a downward biased measure of unemployment duration. We have chosen to use the last definition, but with a somewhat less strict censoring
criterion: individuals are only censored when spending more than two months out of the unemployment register without having an employment record.
14
Some Ž
. inaccuracies in the employers’ register which may be likely for small enterprises
and some potential spurious unemployment registration behaviour is thus allowed
14
Ž .
Hernæs and Strøm 1996 report estimates based on a combination of registers similar to ours. These are compared to estimates where unemployment duration is defined as joblessness, i.e., the time
from an unemployed enters the unemployment register until she shows up in the employers’ register. Joblessness turns out to be their preferred definition, mainly because of endogenous censoring: standard
hazard models assume that censoring is exogenous to the transition in question. If, however, the individuals that drop out from the unemployment register are the ones with less chances on the labour
market, the exogeneity assumption is violated. This, in turn, leaves the estimate of the baseline hazard positively biased. It is hard to evaluate the extent of this problem. Relying on joblessness as the
appropriate definition of unemployment can circumvent the problem. Even so, the extra noise introduced by this approach —counting education, military services, child care, etc. as unemployment
— made us prefer the definition described in the text.
for. This reduces the problem of potentially biasing durations downwards, but obviously without resolving it. It seems that problems of this kind, inherent in the
use of register data, remains whatever definition of unemployment is used, and a reader must bear in mind the consequences of the different definitions when
comparing results from different studies.
The analysis is also complicated by a tendency for individuals to disappear from the unemployment register for a couple of months, and then to turn up again.
These features may reflect that individuals actually leave the labour force, or may be due to errors in the registers. It is not obvious that everyone who leaves the
unemployment register for a couple of months really has been out of the labour
Ž force meanwhile. This is not to say that such behaviour can be completely ruled
. out. To cope with these possible inconsistencies, we assume that periods two
months or less apart belong to the same spell.
15
A transition into employment is then defined as having a record in the employers’ register that begins before
Ž .
Ž .
December 31, 1992 1993 for those who registered on December 1, 1990 1991 . Individuals who registered earlier in the sampling periods are observed for a
period of the same length. Persons with a gap of more than two months between the unemployment and the employment record are, however, treated as censored.
16
In behavioural terms, we regard them as having left the labour force. Obviously, combining the two registers as described affects the number of
transitions and also the length of spells compared to using the ‘‘raw’’ registers. Table 1 reports spell characteristics for first transitions out of the unemployment
register,
17
first transitions into the employers’ register, and the combination used in this paper. Within the observation period, almost all the observed individuals
Ž .
left the unemployment register first panel , and about two-thirds showed up in the Ž
. Ž
. employers’ register second panel . When combining third panel , the number of
transitions is reduced compared to when looking only at records into the employ- ers’ register, but the mean duration of completed spells is shorter.
18
It is important to note that within the framework of a single spell model, the rather few
transitions do not imply that the others did not get a job within the observation period. Those who are censored for the reasons discussed above, may nevertheless
have found employment later, but that is outside the scope of the present analysis.
15
Results from running the model on spells with one month-gaps — not reported here but available on request — increased the number of censorings but otherwise did not affect the results significantly.
16
Some jobs may be relief jobs that are part of labour market programmes. Controlling for this is tricky because there are no clear administrative rules as to whether such jobs should be recorded in the
employers’ register. We have tried to identify ‘‘ordinary’’ jobs by searching for labour market programme records in the unemployment register with a starting date that fall within two months of
the starting date in the employers’ register. In such cases, we use the next employment record, if any.
17
Without any checks for succeeding unemployment records.
18
The ‘‘raw’’ transitions are all censored at the maximum number of observable 4-week periods for those who entered unemployment on December 1, corresponding to 756 days.
E. Bratberg,
K. Vaage
r Labour
Economics 7
2000 153
– 180
162
Table 1 Ž
. Spell characteristics days . Standard deviations in parentheses
Ž .
Ž .
1990 N s9936 1991 N s12054
All With UB
Without UB All
With UB Without UB
Out of unemployment register first record
a
Ž .
Ž .
Ž .
Ž .
Ž .
Ž .
Mean duration, completed spells 160 156
202 170 95 103
183 173 225 185
101 109 a censored spells
330, 3.3 254, 4.2
76, 2.0 518, 4.3
444, 5.5 74, 1.9
Into employers’ register first record
a
Ž .
Ž .
Ž .
Ž .
Ž .
Ž .
Mean duration, completed spells 258 210
270 205 236 217
267 206 275 204
248 210 a censored spells
3572, 36.0 1996, 32.9
1576, 40.7 4459, 37.0
2756, 34.1 1703, 42.8
Into employment — combined registers Ž
. Ž
. Ž
. Ž
. Ž
. Ž
. Mean duration, completed spells
179 167 207 170
116 145 216 190
254 197 142 157
Ž .
Ž .
Ž .
Ž .
Ž .
Ž .
Mean duration, censored spells 322 246
391 249 230 208
346 249 403 247
228 208 a censored spells
6313, 63.5 3598, 59.3
2715, 70.2 7943, 65.9
5340, 66.1 2603, 65.4
a
Censored spells have duration 756 days.
Table 2 Sample characteristics
Standard deviations in parentheses. 1990
1991
a
Ž .
Ž .
Income prev. year 76 726
69 743 80 502
70 832
a
Ž .
Ž .
Ž .
Spouse income if married
133 302 100 695
134 672 106 391
a
Ž .
UBrweek –
– 1462
600 Ž
. Ž
. Years of education
10.7 1.8
10.9 1.9
Ž .
Ž .
Age 29.8
10.8 30.5
10.9 Ž
. Ž
. Years of experience
7.8 7.2
8.5 7.6
Ž .
Ž .
a children -11 0.30
0.67 0.31
0.68 Ž
. Ž
. a children 11, -18
0.16 0.47
0.16 0.47
b
Ž .
Ž .
local unemployment 6.11
2.02 6.71
1.94 female
43.8 40.6
married 28.4
28.5 divorcedrwidow
9.9 10.2
non-Scandinavian 1.95
1.65 UB-receivers
61.1 67.0
in Region 2 21.7
23.3 in Region 3
34.3 32.3
in Region 4 18.6
17.7 Sample size
9936 12 054
a
1989 NoK.
b
Average over spell duration.
After excluding 1152r11 088 and 1550r13 604 observations with missing background information, the 1990 and 1991 samples consist of 9936 and 12054
persons, respectively. A full description of the elements of the covariate vector x
t
is found in Appendix A Table 2 provides descriptive statistics for some important variables, revealing few differences in the sample means. The average person in
the 1991 sample is slightly older, with somewhat longer labour force experience and higher previous earnings, possibly reflecting the increasing national unem-
ployment rate. There are also more females in the 1990 sample. However, the relatively low average age and previous income are conspicuous in both samples.
The low percentage of married persons is complemented by the fact that spouse income for those married averages higher than the sample incomes. Considering
the well-known fact that female labour market behaviour differs from that of males, in the analysis we have added interaction effects between gender and some
variables relevant to family background.
To catch the effect from unemployment benefits, we allow the baseline hazard to be different for UB-receivers and non-receivers,
19
and between the samples.
19
Benefit size was not available for the 1990 sample, and was not used because sample comparisons was the aim of the analysis.
Ž The hypothesis is that being a UB-receiver and belonging to the 1991 post rule
. change sample adds negatively to the exit hazard.
As an indicator of labour demand, we use the monthly local unemployment rate. Where the 4-week periods that the durations are split into do not fall within a
single month, we use a weighted mean of two succeeding months. Although the national unemployment rate showed an increasing trend in the observation period,
there is considerable variation in this variable.
4. Results and discussion
